collaborators

7 papers

cs.HC2026

PersonaTeaming: Supporting Persona-Driven Red-Teaming for Generative AI

Wesley Hanwen Deng, Mingxi Yan, Sunnie S. Y. Kim +5

Recent developments in AI safety research have called for red-teaming methods that effectively surface potential risks posed by generative AI models, with growing emphasis on how r…

cs.CV2026

MM-SCALE: Grounded Multimodal Moral Reasoning via Scalar Judgment and Listwise Alignment

Eunkyu Park, Wesley Hanwen Deng, Cheyon Jin +8

Vision-Language Models (VLMs) continue to struggle to make morally salient judgments in multimodal and socially ambiguous contexts. Prior works typically rely on binary or pairwise…

cs.HC2025

Seeing Twice: How Side-by-Side T2I Comparison Changes Auditing Strategies

Matheus Kunzler Maldaner, Wesley Hanwen Deng, Jason I. Hong +2

While generative AI systems have gained popularity in diverse applications, their potential to produce harmful outputs limits their trustworthiness and utility. A small but growing…

cs.AI2025

PersonaTeaming: Exploring How Introducing Personas Can Improve Automated AI Red-Teaming

Wesley Hanwen Deng, Sunnie S. Y. Kim, Akshita Jha +4

Recent developments in AI governance and safety research have called for red-teaming methods that can effectively surface potential risks posed by AI models. Many of these calls ha…

cs.HC2025

"I Don't Think RAI Applies to My Model'' -- Engaging Non-champions with Sticky Stories for Responsible AI Work

Nadia Nahar, Chenyang Yang, Yanxin Chen +4

Responsible AI (RAI) tools -- checklists, templates, and governance processes -- often engage RAI champions, individuals intrinsically motivated to advocate ethical practices, but…

cs.HC2025

WeAudit: Scaffolding User Auditors and AI Practitioners in Auditing Generative AI

Wesley Hanwen Deng, Wang Claire, Howard Ziyu Han +3

There has been growing interest from both practitioners and researchers in engaging end users in AI auditing, to draw upon users' unique knowledge and lived experiences. However, w…